| Detailed information |
| Pre-requisites |
Kenntnisse über Windows/Mac/Linux und Anwendungsprogramme sowie die Organisation von Ordnern und Dateien werden erwartet.
Knowledge of Windows/Mac/Linux and application programs, as well as the organization of folders and files is expected.
|
| Original study plan |
Master's programme Economic and Business Analytics 2025W |
| Learning Outcomes |
Competences |
- Python Basics: Identify variables, suitable data types, and control structures to implement programs in Python .
- Practical Implementation: Apply python programming concepts through hands-on exercises and projects, using Jupyter notebooks and other tools.
- Problem-Solving: Develop problem-solving skills by working on assignments and projects, and applying Python programming concepts to real-world scenarios.
|
|
| Skills |
Knowledge |
- Learning Outcome 3 (LO3): Demonstrate the understanding of python syntax.
- Learning Outcome 4 (LO4): Assess and apply the appropriate data structures and data type.
- Learning Outcome 5 (LO5): Use appropriate libraries for data analytics.
- Learning Outcome 6 (LO6): Design program code for solving simple programming problems using control structures, data types and algorithms learned in this course.
- Learning Outcome 7 (LO7): Construct programs using programming paradigms such as object oriented programming and functional programming.
|
- Learning Outcome 1 (LO1): Set up a python programming environment.
- Learning Outcome 2 (LO2): Apply the basics of python programming such as variables, data types, and control structures.
|
|
| Criteria for evaluation |
The VL and UE Python Programming for Economic and Business Analytics will be graded in conjunction. The total score for the course is 100 points, with 50 points (50%) allocated to the final exam and the remaining 50 points (50%) to homework exercises. A minimum of 50 points is required to pass the course. The following table details how the final grades are assigned based on the total points earned
| Points | Grade |
|---|
| 87,5 - 100 | 1 |
| 75 - 87 | 2 |
| 62,5 - 74,5 | 3 |
| 50 - 62 | 4 |
| 0 - 49,5 | 5 |
- Exam: The exam is conducted individually, with an option for a retry exam in case of unsatisfactory results or scheduling conflicts.
- The exam includes both theoretical and practical questions involving the implementation of solution algorithms.
- It has a duration of 180 minutes .
- Exercises:
- There are five homework assignments (each worth 8 points) that must be submitted via Moodle. Feedback will also be provided through Moodle.
- An additional 10 points can be earned for presenting the solutions to a previous assignment orally
- The total possible points for exercises is calculated as 5 x 8 + 10 = 50 points.
Synchronisation of learning outcomes and assessments:
- LO1: Final Exam + Exercises
- LO2: Final Exam + Exercises
- LO3: Final Exam + Exercises
- LO4: Final Exam + Exercises
- LO5: Final Exam + Exercises
- LO6: Final Exam + Exercises
- LO7: Final Exam + Exercises
|
| Methods |
The teaching and learning method will integrate instruction with student presentations and exercises to effectively convey the outlined learning outcomes to students and ensure comprehension of the content.
Each appointment will be split into two parts:
- Debriefing: Students (at random) will present their solutions to their previous assignments
- Briefing: Explaining key ideas of upcoming assignment with examples
|
| Language |
English |
| Study material |
|
| Changing subject? |
No |
| Further information |
Attendance is mandatory
Introduction to Software Development in Python consists on the practical exercises and the theoretical part. They are assessed together.
|
| Earlier variants |
They also cover the requirements of the curriculum (from - to)
977PADTPYTU21: UE Python Programming for Economic and Business Analytics (2021W-2022S)
|
